The present disclosure relates generally to a method and apparatus for analyzing three-dimensional (3D) images, and particularly to a method and apparatus for analyzing a 3D image representative of a lesion found in a CT (computed tomography) image of a lung.
CT imaging provides a description of anatomy in great detail and is therefore being increasingly used for detecting and following the evolution of lesions that may be potential cancers. The follow-up of lesion size and other characteristics is being used for determining lesion malignancy, or to assess the effectiveness of a therapeutic regimen. Current algorithms and applications are available for automatically segmenting and sizing solid lung lesions that have been identified by a radiologist in CT images of the lung. For example, “CT Advanced Lung Analysis” (ALA) available from General Electric Company provides such a software tool. Moreover, the ALA software allows the radiologist to compare the size of a lesion over time.
However, such applications only allow for the analysis of solid lesions (S), discarding non-solid (NS) and part-solid (PS) lesions. It has been shown that these discarded lesions are of diagnostic value and are being discovered more often because of increasing image resolution and image quality. The ability to segment and measure only solid lesions leaves a gap in a radiologist's ability to provide diagnostic service due to a large proportion of the part-solid and the non-solid lesions in the total volume of interest (VOI).
While existing tools are suitable for their intended purpose, there remains a need in the art to provide radiologists with tools that allow them to determine solid and non-solid lesion volume and density attributes independently, and to be able to compare them over time.